Analysis of Symptoms and Demographic Characteristics in Diagnosis of COVID-19 by Logistic Regression Model

The new coronavirus COVID-19 is an infectious disease that started spreading globally in December 2019. Some symptoms are known to give clues as to whether the COVID-19 virus is infected. Therefore, the main purpose of this paper was to determine specific symptoms related to COVID-19 for the rapid d...

Full description

Saved in:
Bibliographic Details
Published inSelçuk Üniversitesi Fen Fakültesi Fen Dergisi Vol. 50; no. 1; pp. 1 - 5
Main Author Tanış, Caner
Format Journal Article
LanguageEnglish
Published 24.04.2024
Online AccessGet full text

Cover

More Information
Summary:The new coronavirus COVID-19 is an infectious disease that started spreading globally in December 2019. Some symptoms are known to give clues as to whether the COVID-19 virus is infected. Therefore, the main purpose of this paper was to determine specific symptoms related to COVID-19 for the rapid diagnosis of COVID-19 cases. The data set consists of 25985 individuals including PCR results, 2 demographic properties (age, gender), and 5 symptoms such as headache, shortness of breath, sore throat, fever, and cough is considered in this study. We analyzed the relationship between these covariates and PCR results by binary logistic regression model. A total of 16405 (63.1%) individuals having to positive PCR results were included in this study. The research population was divided into two age groups (
ISSN:2458-9411
2458-9411
DOI:10.35238/sufefd.1335965